Matching Advertisements to Visual Media Objects

ABSTRACT

Systems, methods, and computer-readable media for matching a visual media object to an advertisement are provided. Embodiments of the present invention include receiving un-categorized visual media objects, automatically categorizing received visual media objects into subject-matter categories using image recognition technology, and retrieving advertisements assigned to the same subject-matter category for presentation in association therewith.

BACKGROUND

On the Internet, advertisements are often presented that are based onthe content displayed on a webpage. The goal is to match the subjectmatter of the advertisement with the subject matter of the webpage'scontent. The subject matter of the advertisement is often determinedbased upon keywords that are submitted with and/or extracted from thetextual content of the advertisement. The subject matter of a webpage'scontent is often automatically determined by a computer program thatevaluates words and/or phrases within the textual content of thewebpage. The subject matter of a visual media object, such as an imageor a video, may not be automatically determined as readily, because thevisual media object often lacks textual content. This makes it difficultto automatically match the subject matter of a visual media object withthe subject matter of an advertisement.

SUMMARY

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter.

Embodiments of the present invention generally relate to matchingadvertisements with visual media objects, e.g., digital photographs andvideos. An advertisement is selected to be associated with a visualmedia object by matching the subject matter of the advertisement withthe subject matter of the visual media object at the same level ofspecificity. In general, advertisements are submitted with detailedkeywords that may be used to define a very specific subject matter. Onthe other hand, image recognition technologies utilized to determine thesubject matter of visual media objects may only be capable of placingvisual media objects into more general subject-matter categories. Thus,in accordance with embodiments of the present invention, advertisementsmay be grouped into categories that correlate with the categoriesutilized by the relevant image recognition technology. In this way,visual media objects may be received and assigned a subject matter. Anadvertisement, having been assigned the same subject matter as thevisual media object, may then be matched with the visual media objectand the two may be presented together, if desired.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is described in detail below with reference to theattached drawing figures, wherein:

FIG. 1 is a block diagram of an exemplary computing environment forselecting an advertisement to be associated with a visual media objectthat is suitable for use in implementing embodiments of the presentinvention;

FIG. 2 is a block diagram of an exemplary computing system architecturesuitable for use in implementing embodiments of the present invention;

FIG. 3 is a flow diagram illustrating an exemplary method for selectingan advertisement to be associated with a visual media object, inaccordance with an embodiment of the present invention; and

FIG. 4 is flow diagram illustrating an exemplary method for selecting anadvertisement having the same context as a visual media object, inaccordance with an embodiment of the present invention.

DETAILED DESCRIPTION

The subject matter of the present invention is described withspecificity herein to meet statutory requirements. However, thedescription itself is not intended to limit the scope of this patent.Rather, the inventors have contemplated that the claimed subject mattermight also be embodied in other ways, to include different steps orcombinations of steps similar to the ones described in this document, inconjunction with other present or future technologies. Moreover,although the terms “step” and/or “block” may be used herein to connotedifferent elements of methods employed, the terms should not beinterpreted as implying any particular order among or between varioussteps herein disclosed unless and except when the order of individualsteps is explicitly described.

Accordingly, in one embodiment, the present invention relates tocomputer storage media having computer-executable instructions embodiedthereon for performing a method of selecting advertisements to beassociated with visual media objects. The method includes receiving avisual media object and assigning a subject-matter category to thevisual media object using automated image recognition. The method alsoincludes, retrieving an advertisement that is assigned the samesubject-matter category as the visual media object to be associated withthe visual media object. The method further includes, storing theadvertisement in association with the visual media object.

In another embodiment, the present invention relates to a computerizedmethod for selecting advertisements having the same context as visualmedia objects. The method includes categorizing one or moreadvertisements into a set of subject-matter categories, and assigning animportance value to each subject-matter category. The method furtherincludes, classifying one or more of the visual media objects into afirst subject-matter category that has an importance value of at least athreshold value, retrieving a categorized advertisement from the firstsubject-matter category, and storing the categorized advertisement inassociation with the appropriate subject-matter category.

In yet another embodiment, the present invention relates to acomputerized system for retrieving advertisements having the samesubject matter as visual media objects. The system includes anadvertisement receiving component for receiving a plurality ofadvertisements and one or more keywords associated with each of theadvertisements and for storing the advertisements and associatedkeywords in association with one another. The system also includes anadvertisement categorizing component for categorizing the plurality ofadvertisements into subject-matter categories using the respectivelyassociated keywords. The system further includes, a media receivingcomponent for receiving a plurality of visual media objects and a mediacategorizing component for categorizing the plurality of visual mediaobjects into the subject-matter categories. Finally, the system includesan advertisement retrieval component for retrieving a categorizedadvertisement having the same subject-matter category as one or more ofthe plurality of visual media objects.

Having briefly described an overview of embodiments of the presentinvention, an exemplary operating environment suitable for use inimplementing embodiments of the present invention is described below.

Referring to the drawings in general, and initially to FIG. 1 inparticular, an exemplary operating environment for implementingembodiments of the present invention is shown and designated generallyas computing device 100. Computing device 100 is but one example of asuitable computing environment and is not intended to suggest anylimitation as to the scope of use or functionality of the invention.Neither should the computing environment 100 be interpreted as havingany dependency or requirement relating to any one or combination ofcomponents illustrated.

The invention may be described in the general context of computer codeor machine-useable instructions, including computer-executableinstructions such as program components, being executed by a computer orother machine, such as a personal data assistant or other handhelddevice. Generally, program components including routines, programs,objects, components, data structures, and the like, refer to code thatperforms particular tasks, or implement particular abstract data types.Embodiments of the present invention may be practiced in a variety ofsystem configurations, including hand-held devices, consumerelectronics, general-purpose computers, specialty computing devices,etc. Embodiments of the invention may also be practiced in distributedcomputing environments where tasks are performed by remote-processingdevices that are linked through a communications network.

With continued reference to FIG. 1, computing device 100 includes a bus110 that directly or indirectly couples the following devices: memory112, one or more processors 114, one or more presentation components116, input/output (I/O) ports 118, I/O components 120, and anillustrative power supply 122. Bus 110 represents what may be one ormore busses (such as an address bus, data bus, or combination thereof).Although the various blocks of FIG. 1 are shown with lines for the sakeof clarity, in reality, delineating various components is not so clear,and metaphorically, the lines would more accurately be grey and fuzzy.For example, one may consider a presentation component such as a displaydevice to be an I/O component. Also, processors have memory. Theinventors hereof recognize that such is the nature of the art, andreiterate that the diagram of FIG. 1 is merely illustrative of anexemplary computing device that can be used in connection with one ormore embodiments of the present invention. Distinction is not madebetween such categories as “workstation,” “server,” “laptop,” “hand-helddevice,” etc., as all are contemplated within the scope of FIG. 1 andreference to “computer” or “computing device.”

Computing device 100 typically includes a variety of computer-readablemedia. By way of example, and not limitation, computer-readable mediamay comprise Random Access Memory (RAM); Read Only Memory (ROM);Electronically Erasable Programmable Read Only Memory (EEPROM); flashmemory or other memory technologies; CDROM, digital versatile disks(DVDs) or other optical or holographic media; magnetic cassettes,magnetic tape, magnetic disk storage or other magnetic storage devices,or any other medium that can be used to encode desired information andbe accessed by computing device 100.

Memory 112 includes computer storage media in the form of volatileand/or nonvolatile memory. The memory may be removable, non-removable,or a combination thereof. Exemplary hardware devices include solid-statememory, hard drives, optical-disc drives, etc. Computing device 100includes one or more processors that read data from various entitiessuch as memory 112 or I/O components 120. Presentation component(s) 116present data indications to a user or other device. Exemplarypresentation components include a display device, speaker, printingcomponent, vibrating component, etc. I/O ports 118 allow computingdevice 100 to be logically coupled to other devices including I/Ocomponents 120, some of which may be built in. Illustrative componentsinclude a microphone, joystick, game pad, satellite dish, scanner,printer, wireless device, etc.

Turning now to FIG. 2, a block diagram is illustrated that shows anexemplary computing system architecture 200 suitable for matching anadvertisement with a visual media object, in accordance with anembodiment of the present invention. It will be understood andappreciated by those of ordinary skill in the art that the computingsystem architecture 200 shown in FIG. 2 is merely an example of onesuitable computing system and is not intended to suggest any limitationas to the scope of the use or functionality of the present invention.Neither should the computing system architecture 200 be interpreted ashaving any dependency or requirement related to any singlecomponent/module or combination of component/modules illustratedtherein.

Computing system architecture 200 includes system input data 210, acomputing environment 220, and output data 230. Computing environment220 may be a single computing device, such as computing device 100 shownin FIG. 1. In the alternative, computing environment 220 may be adistributed computing environment that includes multiple computingdevices coupled with one another via one or more networks. Such networksmay include, without limitation, one or more local area networks (LANs)and/or one or more wide area networks (WANs). Such network environmentsare commonplace in offices, enterprise/wide computer networks,intranets, and the Internet. Accordingly, the network, or combination ofnetworks, is not further described herein.

The system input data 210 shown in FIG. 2 includes an un-categorizedimage 211, an un-categorized video 212, a training image 213, a trainingvideo 214, an advertisement with one or more associated keywords 216,and an advertisement with an associated subject-matter category 218. Thesystem input data 210 may be transferred to the computing environment220 in a variety of manners. In one embodiment, the system input data210 are transferred to computing environment 220 through a network,e.g., the Internet. In another embodiment, the system input data 210 aretransferred to computing environment 220 through a removable memory,such as a CD, Floppy disk, or Flash drive. In yet another embodiment,the system input data 210 are entered using a keyboard that iscommunicatively coupled to a computing device within computingenvironment 220. A user interface may be provided to facilitate thetransfer of system input data 210 to a computing device within thecomputing environment 220. The system input data 210 may be transferredfrom one program to a component within computing environment 220. Inthat instance, the program could be within computing environment 220 oron a separate computing device (not shown) that is communicativelycoupled to computing environment 220.

As shown in FIG. 2, the computing environment 220 includes a mediareceiving component 222, a media categorizing component 224, anadvertisement retrieving component 226, an importance value determiningcomponent 227, an advertisement categorizing component 228, anadvertisement receiving component 229, and a database 240. In someembodiments, one or more of the illustrated components, may beimplemented as stand-alone applications. In other embodiments, one ormore of the illustrated components, may be integrated directly into theoperating system of one or more computing devices within computingenvironment 220. It will be understood by those of ordinary skill in theart that the components 222, 224, 226, 227, 228, and 229, illustrated inFIG. 2 are exemplary in nature and in number and should not be construedas limiting. Any number of components may be employed to achieve thedesired functionality within the scope of embodiments of the presentinvention. In addition, each component may reside on more than onecomputing devices within computing environment 220.

The media receiving component 222 is configured for receiving visualmedia objects. Visual media objects may be in the form of images, videoor a combination thereof. In one embodiment, the media receivingcomponent 222 receives one or more training images 213 and/or trainingvideos 214 that are used to train the media categorizing component 224.In another embodiment, the media receiving component 222 receives one ormore un-categorized images 211 and/or un-categorized videos 212. Wheneither un-categorized videos 212 or training videos 214 are received,the media receiving component 222 may perform a key frame extractionprocess that finds key frames that are distinctive and representative ofthe video subject matter. The key frame extractions are performed as apreparatory step for the media categorizing component 224 that analyzesthe key frames rather than every frame in the video. In embodiments,other preparatory steps may also be performed by the media receivingcomponent 222 as needed.

The media categorizing component 224 is configured to categorizeun-categorized images 211 or un-categorized videos 212 intosubject-matter categories. Before the media categorizer component 224may be used to classify un-categorized images 211 or un-categorizedvideos 212, it generally will first be trained using training images 213and training videos 214. Generally, the training images 213 and trainingvideos 214 are manually pre-classified into subject-matter categories.The media categorizing component 224 may break down the image intovarious descriptors. Descriptors include sharp edges, soft edges,colors, large blocks of colors, and other such identifying featuresassociated with the image. The media categorizing component 224 mayprocess the visual media object through shape extraction, spacepartitioning and object recognition algorithms and determine asubject-matter category relevant to the visual media object utilizingone or more of a set of rules and learning algorithms. Using thetraining images 213 and/or training videos 214, the media categorizingcomponent 224 learns what descriptors are common to the respectivesubject-matter categories.

Once the media categorizing component 224 is trained, it may then beused to classify un-categorized images 211 or un-categorized videos 212into subject-matter categories based on the descriptors identified inthe un-categorized visual media object. Once in operation, the mediacategorizing component 224 may be continually improved throughadditional training methods. Subject-matter categories may be added orremoved as desired. The media categorizer component 224 may receive theunclassified images 211 or un-classified videos 212 from the mediareceiving component 222 which may perform preparatory steps on thevideos as described above.

In one embodiment, the media categorizer component 224 is only trainedto classify un-categorized images 211 or un-categorized videos 212 intosubject-matter categories that have an objective importance, forinstance, a sufficient commercial demand, assigned by importance valuedetermining component 227, above a pre-determined threshold value. Theoperation of the importance value determining component 227 is explainedin more detail hereafter. In addition, if a sufficient number oftraining images 213 or training videos 214 are not available for aparticular subject-matter category, then that subject-matter categorymay be abandoned or combined into a related category. Relatedsubject-matter categories may also be combined if the media categorizercomponent 224 is unable to reliably distinguish between two similarsubject-matter categories.

The advertisement receiving component 229 is configured to receiveadvertisements with associated keywords 216 or advertisements withassociated subject-matter categories 218. The advertisements may bereceived over an Internet connection or other method. In one embodiment,advertisements are submitted to the advertisement receiving component229 along with associated keywords and/or categories through a userinterface provided by the advertisement receiving component 229. In someembodiments, the advertisement receiving component 229 stores theadvertisements along with their associated keywords and categories in adatabase, for instance, database 240. The advertisement receivingcomponent 229 may also pass the advertisements directly to theadvertisement categorizing component 228.

The advertisement categorizing component 228 is configured to categorizeadvertisements into subject-matter categories using the keywords thatare submitted with the respective advertisements. The subject-mattercategories may be organized hierarchically. By way of example, and notlimitation, the advertisement categorizing component 228 may useclassification algorithms such as the support vector machine (SVM),trigram, the Bayesian Algorithm, or other suitable classificationalgorithm. The advertisement categorizing component 228 may receive theadvertisements and keywords directly from the advertisement receivingcomponent 229 or may retrieve the advertisements and keywords from thedatabase 240. The advertisement categorizing component 228 may outputthe advertisements sorted by subject-matter categories into a list 236that may then be stored in a table within database 240 or otherwiseaccessed by users directly, for example through a user interface orprint out.

The importance value determining component 227 is configured todetermine an importance value for each of the subject-matter categoriesrelative to one another and/or a predetermined threshold value. Suchdetermination may be made, for instance, based upon commercialadvertising demand. Commercial advertising demand may be determined byweighing a variety of factors including, but not limited to, the numberof advertisers submitting advertisements within a particularsubject-matter category assigned thereto, the probability that anadvertisement having a particular category assigned thereto will beselected by a viewer, the number of advertisements within a particularsubject-matter category, and an objective importance of advertisementshaving a particular category assigned thereto, such importance beingbased, for instance, on the amount of money that advertisers are willingto pay to have the advertisements within a subject-matter categorypresented or a monetization value associated with advertisements havingthe particular category assigned thereto. The importance valuedetermining component 227 is configured to determine an importance valuefor each subject-matter category used by the advertisement categorizingcomponent 228. In one embodiment, the importance value reflects thecommercial value of the subject-matter category. Thus, a high importancevalue would be assigned to a subject-matter category that has a lot ofadvertisers that are willing to pay relatively high amounts of money forthere advertisements to be presented. Subject-matter categories with animportance value above a threshold value may be classified as highlyimportant. In one embodiment, visual media objects are categorized onlyinto highly important categories. The importance value determiningcomponent 227 may receive the subject-matter categories fromadvertisement categorization component 228, directly from database 240,or though any other available method within the scope of embodimentshereof. The output from the importance value determining component 227may be a list ranking the subject-matter categories 234 with respect toone another, a list indicating those subject-matter categories that havean importance value only above and/or below a threshold value, or anycombination thereof. The output may be stored in the database 240, oroutput as a file directly to a user or other application.

The advertisement retrieving component 226 receives the subject-matterclassification assigned to the un-categorized visual media object by themedia categorizing component 224, and retrieves a categorizedadvertisement 232 from the same subject-matter category. In oneembodiment, the advertisement retrieving component 226 retrieves thecategorizedl advertisement from the database 240.

The database 240 is configured to store advertisements along withassociated keywords and subject-matter categories. In some embodiments,un-categorized images 211, un-categorized videos 212, training images213, and training videos 214 are stored in association with the database240. The database 240 maybe accessed by components 222, 224, 226, 227,228, and 229 as needed. All system input data 210 and output data 230,as well as intermediary data, maybe stored temporarily or permanently inthe database 240. In some embodiments, the database 240 is configured tobe searchable for one or more of the items stored in associationtherewith. It will be understood and appreciated by those of ordinaryskill in the art that the information stored in the database 240 may beconfigurable and may include any information relevant to theadvertisements, visual media objects, components 222, 224, 226, 227,228, and 229, system input data 210 and output data 230. The content andvolume of such information are not intended to limit the scope ofembodiments of the present invention in any way. Further, thoughillustrated as a single independent component, the database 240 may, infact, be a plurality of databases, for instance, a database cluster,portions of which may reside on a plurality of computing devices.

Referring next to FIG. 3, a flow diagram showing an exemplary method forselecting an advertisement is illustrated and designated generally asreference numeral 300. At step 310, a visual media object is received. Avisual media object is a media object that communicates its contentthrough a display that may be viewed. Visual media objects may generallybe divided into two categories: images and videos. Images contain visualrepresentations that do not change or move when viewed. The image may bein a file type that is capable of display by a web browser. Examples ofsuch file types, include, but are not limited to, a GIF, JPEG, TIF orSVG file formats. A video contains visual representations that changeand/or move when viewed. Audio content may also be associated with thevisual media object, as with the sound track on a movie or video. Thevideo may be in a file type that is capable of display by a web browser,one example of which is the MPEG format.

At step 320, the visual media object is assigned a subject-mattercategory using an automated image recognition application. The visualmedia object is classified into a subject-matter category for whichadvertisements are available for presentation. Prior to operation, theautomated image recognition application is trained to classifyun-categorized visual media objects into subject-matter categories usingtraining images 213 and training videos 214 that have been manuallyassigned a subject-matter category. In one embodiment, the visual mediaobject is assigned to a subject-matter category that has an objectiveimportance value, for instance, a commercial demand rank, above adesignated threshold value.

At step 330, an advertisement assigned the same subject-matter categoryas the visual media object, is retrieved. The advertisement may beretrieved from a database, such as database 240, that containsadvertisements that have been assigned subject-matter categories. Atstep 340, the advertisement is stored in association with the visualmedia object (or an identifier thereof) for later use. In oneembodiment, advertisements are continually received in association withrelevant keywords and/or subject-matter categories. If the advertisementis associated with only keywords, the advertisement is then categorizedinto a subject-matter category using the keywords. The categorizationprocess may be performed automatically using any state of the artclassifying algorithm such as SVM (Support Vector Machine), a trigram,or other method. The advertisements should be categorized intosubject-matter categories no more specific than can accurately beidentified by the image recognition application. As image recognitionapplications improve, the subject-matter categories may become morespecific.

In one embodiment, the subject-matter categories are ranked relative toone another and/or a pre-determined threshold value based on one or moreindicators of objective importance, for instance, commercial advertisingdemand. Commercial advertising demand may be calculated based on anumber of factors that include, but are not limited to, the number ofadvertisements within a subject-matter category, the number ofadvertisers submitting advertisements with a subject-matter category,the probability of an advertisement having a particular subject-mattercategory assigned thereto being clicked by a viewer, a frequency withwhich an advertisement with the subject-matter category assigned theretowill be clicked by a viewer, a frequency with which viewers convert inresponse to seeing an advertisement with the subject-matter categoryassigned thereto, and an objective importance of advertisements within aparticular category, for instance, determined by the amount of moneyadvertisers are willing to pay to have advertisements within thesubject-matter category presented. In one embodiment, the un-categorizedvisual media object is only classified into categories that have beenassigned an importance value (e.g., a commercial demand rank) above athreshold value. The threshold value may be set, for instance, at apoint where the expense to set up, and operate embodiments of thepresent invention, is more than offset by the increase in advertisingrevenue likely to result from matching advertisements with previouslyun-categorized visual media objects. As the cost of setting up andoperating embodiments of the present invention decreases, more and moresubject-matter categories may become commercially viable.

In one embodiment, an un-categorized visual media object on a webpage orwithin a web server is selected for pre-classification. Theun-categorized visual media object is retrieved and assigned asubject-matter category, as in step 320. The subject-matter categoryassigned to the visual media object may be tracked using a table orother method. The table may be accessed when a visual media object isreceived to see if the visual media object has already been assigned asubject-matter category. In another embodiment, the visual media objectis categorized in real time as it is displayed.

Referring next to FIG. 4, a flow diagram showing an exemplary method forselecting an advertisement in the same context as a visual media objectis illustrated and designated generally as reference numeral 400. Atstep 410, individual advertisements, within a group of advertisements,are categorized by subject matter. In one embodiment, the advertisementshave been previously submitted for online advertising. Theadvertisements are submitted with keywords or categories that are usedto define the subject matter of the advertisement. The advertisingcategorization process may be coordinated with an image categorizationprocess so that the two processes use the same subject-mattercategories. The subject-matter categories into which the advertisementsare categorized should be no more specific than the image categorizationtechnology is capable of differentiating between. Once advertisingcategories have been established, a user interface may be provided toallow the advertiser to submit a new advertisement and select a categoryto associate with the advertisement.

At step 420, an importance value is assigned to each subject-mattercategory. Assigning an importance value, for instance, based upon acommercial demand rank, to a subject-matter category was explainedhereinabove with reference to FIG. 3. At step 430, a visual media objectis classified into a first subject-matter category that has animportance value at or above a pre-determined threshold value.Subject-matter categories below the importance value threshold are notused. At step 440, an advertisement from the same subject-mattercategory into which the visual media object is classified is retrieved.The advertisement may be retrieved from a database, such as database240. This advertisement is then stored in association with the visualmedia object (or an identifier thereof) at step 450.

The present invention has been described in relation to particularembodiments, which are intended in all respects to be illustrativerather than restrictive. Alternative embodiments will become apparent tothose of ordinary skill-in-the-art to which the present inventionpertains without departing from its scope.

From the foregoing, it will be seen that this invention is one welladapted to attain all the ends and objects set forth above, togetherwith other advantages which are obvious and inherent to the system andmethod. It will be understood that certain features and sub-combinationsare of utility and may be employed without reference to other featuresand sub-combinations. This is contemplated by and is within the scope ofthe claims.

1. One or more computer-storage media having computer-executableinstructions embodied thereon for performing a method of selectingadvertisements to be associated with visual media objects, the methodcomprising: receiving a visual media object; assigning a subject-mattercategory to the visual media object using automated image recognition;retrieving an advertisement to be associated with the visual mediaobject, wherein the advertisement is assigned the same subject-mattercategory as the visual media object; and storing the advertisement inassociation with the visual media object.
 2. The one or morecomputer-storage media of claim 1, wherein the visual media objectincludes one or more of an image and a video.
 3. The one or morecomputer-storage media of claim 1, wherein assigning the subject-mattercategory to the visual media object further comprises: processing thevisual media object through one or more of shape extraction, spacepartitioning and object recognition algorithms; and determining at leastone subject-matter category relevant to the visual media objectutilizing one or more of a set of rules and learning algorithms.
 4. Theone or more computer-storage media of claim 1, wherein the methodfurther comprises: receiving a new advertisement and one or morekeywords therewith; classifying the new advertisement into thesubject-matter category using the one or more keywords: storing the newadvertisement in association with the subject-matter category.
 5. Theone or more computer-storage media of claim 1, wherein the methodfurther comprises: receiving a new advertisement and the subject-mattercategory associated with the new advertisement, wherein thesubject-matter category is assigned by an entity submitting theadvertisement.
 6. The one or more computer-storage media of claim 1,wherein the method further comprises: classifying a plurality ofadvertisements into subject-matter categories based on the one or morekeywords associated with each advertisement.
 7. The one or morecomputer-storage media of claim 6, wherein the method further comprises:determining an importance value for each of the subject-mattercategories
 8. A computerized system for retrieving advertisements havingthe same subject matter as visual media objects, the system comprising:an advertisement receiving component for receiving a plurality ofadvertisements and one or more keywords associated with each of theadvertisements, and for storing the plurality of advertisements and theone or more keywords in association with one another; an advertisementcategorizing component for categorizing the plurality of advertisementsinto subject-matter categories using the one or more keywords associatedwith the advertisements; a media receiving component for receiving aplurality of visual media objects; a media categorizing component forcategorizing the plurality of visual media objects into thesubject-matter categories; and an advertisement retrieval component forretrieving a categorized advertisement having the same subject-mattercategory as one or more of the plurality of visual media objects.
 9. Thecomputerized system of claim 8, wherein the advertisement receivingcomponent is further for receiving the plurality of advertisements andthe subject-matter category into which the plurality of advertisementsis classified, wherein an advertisement is classified into thesubject-matter category by an entity submitting the advertisement. 10.The computerized system of claim 8, further comprising an importancevalue determining component for: determining an importance value foreach of the subject-matter categories; and assigning a highly importantstatus to the subject-matter categories having the importance valueabove a threshold value.
 11. The computerized system of claim 10,wherein the importance value of the subject-matter category is based onone or more factors including: a number of advertisements having thesubject-matter category assigned thereto; a probability thatadvertisements having the subject-matter category assigned thereto willbe selected by a viewer; a frequency with which an advertisement withthe subject-matter category assigned thereto will be clicked by aviewer; a frequency with which viewers convert in response to seeing anadvertisement with the subject-matter category assigned thereto; anobjective importance of advertisements having the subject-mattercategory assigned thereto; and a number of advertisers havingadvertisements with the subject-matter category assigned thereto. 12.The computerized system of claim 10, wherein the media categorizingcomponent is further for categorizing the plurality of visual mediaobjects only into the subject-matter categories with the highlyimportant status.
 13. The computerized system of claim 12, wherein thehighly important status of a subject-matter category is reevaluated whendata within the one or more factors used to calculate the importancevalue changes.
 14. The computerized system of claim 8, wherein each ofthe plurality of visual media objects include one or more of an imageand a video.
 15. A computerized method for selecting advertisementshaving the same context as visual media objects, the method comprising:categorizing one or more advertisements into a set of subject-mattercategories based on one or more keywords associated with eachadvertisement; assigning an importance value to each subject-mattercategory; classifying a visual media object into a first subject-mattercategory that has the importance value of at least a threshold value;retrieving a categorized advertisement from the first subject-mattercategory; and storing the categorized advertisement in association withthe visual media object.
 16. The method of claim 15, wherein the visualmedia object includes one or more of an image and a video.
 17. Themethod of claim 15, wherein the method further comprises calculating theimportance value of the subject-matter category based on one or morefactors including: a number of advertisements having the subject-mattercategory assigned thereto; a probability that advertisements having thesubject-matter category assigned thereto will be selected by a viewer; afrequency with which an advertisement with the subject-matter categoryassigned thereto will be clicked by a viewer; a frequency with whichviewers convert in response to seeing an advertisement with thesubject-matter category assigned thereto; an objective importance ofadvertisements having the subject-matter category assigned thereto; anda number of advertisers having advertisements with the subject-mattercategory assigned thereto.
 18. The method of claim 17, wherein themethod further comprises: updating the importance value for eachsubject-matter category when data within the one or more factors used tocalculate the importance value changes.
 19. The method of claim 15,wherein the method further comprises receiving an advertisement and atleast one or more of an associated keyword and subject-matter category.20. The method of claim 15, wherein classifying the visual media objectinto a subject-matter category further comprises: identifying one ormore descriptors associated with the visual media object; anddetermining at least one subject-matter category relevant to the visualmedia object utilizing the one or more descriptors.